MétaCan
Menu
Back to cohort
Record W3125530977 · doi:10.1163/15718107-08401002

Military Targeting in the Context of Self-Defence Actions

2015· article· en· W3125530977 on OpenAlexaff
James Green, Christopher Waters

Bibliographic record

VenueNordic Journal of International Law · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsJus ad bellumProportionality (law)CLARITYLawInternational lawContext (archaeology)Public international lawPolitical scienceLaw of warLaw and economicsJust war theoryInternational humanitarian lawSelf defenseUse of forceSociologySpanish Civil War

Abstract

fetched live from OpenAlex

For self-defence actions to be lawful, they must be directed at military targets. The absolute prohibition on non-military targeting under the jus in bello is well known, but the jus ad bellum also limits the target selection of states conducting defensive operations. Restrictions on targeting form a key aspect of the customary international law criteria of necessity and proportionality. In most situations, the jus in bello will be the starting point for the definition of a military targeting rule. Yet it has been argued that there may be circumstances when the jus ad bellum and the jus in bello do not temporally or substantively overlap in situations of self-defence. In order to address any possible gaps in civilian protection, and to bring conceptual clarity to one particular dimension of the relationship between the two regimes, this article explores the independent sources of a military targeting rule. The aim is not to displace the jus in bello as the ‘lead’ regime on how targeting decisions must be made, or to undermine the traditional separation between the two ‘war law’ regimes. Rather, conceptual light is shed on a sometimes assumed but generally neglected dimension of the jus ad bellum ’s necessity and proportionality criteria that may, in limited circumstances, have significance for our understanding of human protection during war.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.327
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNordic Journal of International LawSame topicInternational Law and Human RightsFrench-language works237,207